GVS : A flexible, low-end, 3D visualisation framework for enhancing conceptual groundwater models for community, management and simulations

In this paper we discuss an advanced, 3D groundwater visualisation and animation system that allows scientists, government agencies and community groups to better understand the groundwater processes that effect community planning and decision-making. The system is unique in that it has been designed to optimise community engagement. Although it incorporates a powerful visualisation engine, this open-source system can be freely distributed and boasts a simple user interface allowing individuals to run and investigate the models on their own PCs and gain intimate knowledge of the groundwater systems. The initial version of the Groundwater Visualisation System (GVS v1.0), was developed from a coastal delta setting (Bundaberg, QLD), and then applied to a basalt catchment area (Obi Obi Creek, Maleny, QLD). Several major enhancements have been developed to produce higher quality visualisations, including display of more types of data, support for larger models and improved user interaction. The graphics and animation capabilities have also been enhanced, notably the display of boreholes, depth logs and time-series water level surfaces. The GVS software remains under continual development and improvement

Developing a competitive city through healthy decision-making

This chapter investigates the challenges and opportunities associated with planning for a competitive city. The chapter is based on the assumption that a healthy city is a fundamental prerequisite for a competitive city. Thus, it is critical to examine the local determinants of health and factor these into any planning efforts. The main focus of the chapter is on the role of e-health planning, by utilising web-based geographic decision support systems. The proposed novel decision support system would provide a powerful and effective platform for stakeholders to access essential data for decision-making purposes. The chapter also highlights the need for a comprehensive information framework to guide the process of planning for healthy cities. Additionally, it discusses the prospects and constraints of such an approach. In summary, this chapter outlines the potential insights of using information science-based framework and suggests practical planning methods, as part of a broader e-health approach for improving the health characteristics of competitive cities.

Improving governance : practical methods and an analytic framework for the enhancement of democracy

Seven endemic governance problems are shown to be currently present in governments around the globe and at any level of government as well (for example municipal, federal). These problems have their roots traced back through more than two thousand years of political, specifically ‘democratic’, history. The evidence shows that accountability, transparency, corruption, representation, campaigning methods, constitutionalism and long-term goals were problematic for the ancient Athenians as well as modern international democratisation efforts encompassing every major global region. Why then, given the extended time period humans have had to deal with these problems, are they still present? At least part of the answer to this question is that philosophers, academics and NGOs as well as MNOs have only approached these endemic problems in a piecemeal manner with a skewed perspective on democracy. Their works have also been subject to the ebbs and flows of human history which essentially started and stopped periods of thinking. In order to approach the investigation of endemic problems in relation to democracy (as the overall quest of this thesis was to generate prescriptive results for the improvement of democratic government), it was necessary to delineate what exactly is being written about when using the term ‘democracy’. It is common knowledge that democracy has no one specific definition or practice, even though scholars and philosophers have been attempting to create a definition for generations. What is currently evident, is that scholars are not approaching democracy in an overly simplified manner (that is, it is government for the people, by the people) but, rather, are seeking the commonalities that democracies share, in other words, those items which are common to all things democratic. Following that specific line of investigation, the major practiced and theoretical versions of democracy were thematically analysed. After that, their themes were collapsed into larger categories, at which point the larger categories were comparatively analysed with the practiced and theoretical versions of democracy. Four democratic ‘particles’ (selecting officials, law, equality and communication) were seen to be present in all practiced and theoretical democratic styles. The democratic particles fused with a unique investigative perspective and in-depth political study created a solid conceptualisation of democracy. As such, it is argued that democracy is an ever-present element of any state government, ‘democratic’ or not, and the particles are the bodies which comprise the democratic element. Frequency- and proximity-based analyses showed that democratic particles are related to endemic problems in international democratisation discourse. The linkages between democratic particles and endemic problems were also evident during the thematic analysis as well historical review. This ultimately led to the viewpoint that if endemic problems are mitigated the act may improve democratic particles which might strengthen the element of democracy in the governing apparatus of any state. Such may actively minimise or wholly displace inefficient forms of government, leading to a government specifically tailored to the population it orders. Once the theoretical and empirical goals were attained, this thesis provided some prescriptive measures which government, civil society, academics, professionals and/or active citizens can use to mitigate endemic problems (in any country and at any level of government) so as to improve the human condition via better democratic government.

The importance of project governance framework in project procurement planning

Project Procurement is a ‘great’ environment for ethical issues with its low-price state of mind and competition. It has many opportunities that could contribute to illegal activities or unethical behavior especially in the construction industry. In 2006 alone, 17.3% of 417 Malaysian government contract projects were considered sick due to the poor performance by the contractors. Therefore it is important to govern the project procurement, especially the plan procurement stage to ensure the accountability and transparency of the decision made in awarding the right contract to the best contractor. This is where project governance framework (PGF) is really needed in project procurement planning. Project governance is a subset of corporate governance focusing on the areas of corporate governance related to project activities, including: portfolio direction, project sponsorship, project and program management and efficiency and disclosure and reporting. This paper highlights the importance of implementing project governance framework (PGF) to ensure that the decision makers are answerable and accountable to the stakeholders, and the decision making is transparent to avoid any ethical issues arises. A comprehensive preliminary literature is carried out to discover the importance of executing PGF in project procurement in Malaysian public sector. By understanding the important of PGF, it is hoped that this will bring a signal to other developing countries to implement the similar method in ensuring the transparency of the decision making in project procurement planning in their countries.

Sustainability : driver for decision making in infrastructure

With the growing importance of sustainability assessment in the construction industry, many green building rating schemes have been adopted in the building sector of Australia. However, there is an abnormal delay in the similar adoption in the infrastructure sector. This prolonged delay in practice poses a challenge in mapping the project objectives with sustainability outcomes. Responding to the challenge of sustainable development in infrastructure, it is critical to create a set of decision indicators for sustainability in infrastructure, which to be used in conjunction with the emerging infrastructure sustainability assessment framework of the Australian Green Infrastructure Council. The various literature sources confirm the lack of correlation between sustainability and infrastructure. This theoretical missing link signifies the crucial validation of the interrelationship and interdependency in sustainability, decision making and infrastructure. This validation is vital for the development of decision indicators for sustainability in infrastructure. Admittedly, underpinned by the serious socio-environmental vulnerability, the traditional focus on economic emphasis in infrastructure development needs to be drifted towards the appropriate decisions for sustainability enhancing the positive social and environmental outcomes. Moreover, the research findings suggest sustainability being observed as powerful socio-political and influential socio-environmental driver in deciding the infrastructure needs and its development. These newly developed sustainability decision indicators create the impetus for change leading to sustainability in infrastructure by integrating the societal cares, environmental concerns into the holistic financial consideration. Radically, this development seeks to transform principles into actions for infrastructure sustainability. Lastly, the thesis concludes with knowledge contribution in five significant areas and future research opportunities. The consolidated research outcomes suggest that the development of decision indicators has demonstrated sustainability as a pivotal driver for decision making in infrastructure.

Information dependencies between architects and services engineers for early design evaluation : a framework for an energy design tool for architects

Effective strategies for the design of effi cient and environmentally sensitive buildings require a close collaboration between architects and engineers in the design of the building shell and environmental control systems at the outset of projects. However, it is often not practical for engineers to be involved early on in the design process. It is therefore essential that architects be able to perform preliminary energy analyses to evaluate their proposed designs prior to the major building characteristics becoming fi xed. Subsequently, a need exists for a simplifi ed energy design tool for architects. This paper discusses the limitations of existing analysis software in supporting early design explorations and proposes a framework for the development of a tool that provides decision support by permitting architects to quickly assess the performance of design alternatives.

Asset health prediction using condition indicators and operating environment indicators : a case study

Prognostics and asset life prediction is one of research potentials in engineering asset health management. We previously developed the Explicit Hazard Model (EHM) to effectively and explicitly predict asset life using three types of information: population characteristics; condition indicators; and operating environment indicators. We have formerly studied the application of both the semi-parametric EHM and non-parametric EHM to the survival probability estimation in the reliability field. The survival time in these models is dependent not only upon the age of the asset monitored, but also upon the condition and operating environment information obtained. This paper is a further study of the semi-parametric and non-parametric EHMs to the hazard and residual life prediction of a set of resistance elements. The resistance elements were used as corrosion sensors for measuring the atmospheric corrosion rate in a laboratory experiment. In this paper, the estimated hazard of the resistance element using the semi-parametric EHM and the non-parametric EHM is compared to the traditional Weibull model and the Aalen Linear Regression Model (ALRM), respectively. Due to assuming a Weibull distribution in the baseline hazard of the semi-parametric EHM, the estimated hazard using this model is compared to the traditional Weibull model. The estimated hazard using the non-parametric EHM is compared to ALRM which is a well-known non-parametric covariate-based hazard model. At last, the predicted residual life of the resistance element using both EHMs is compared to the actual life data.

Bayesian filtering over compressed appearance states

This paper presents a framework for performing real-time recursive estimation of landmarks’ visual appearance. Imaging data in its original high dimensional space is probabilistically mapped to a compressed low dimensional space through the definition of likelihood functions. The likelihoods are subsequently fused with prior information using a Bayesian update. This process produces a probabilistic estimate of the low dimensional representation of the landmark visual appearance. The overall filtering provides information complementary to the conventional position estimates which is used to enhance data association. In addition to robotics observations, the filter integrates human observations in the appearance estimates. The appearance tracks as computed by the filter allow landmark classification. The set of labels involved in the classification task is thought of as an observation space where human observations are made by selecting a label. The low dimensional appearance estimates returned by the filter allow for low cost communication in low bandwidth sensor networks. Deployment of the filter in such a network is demonstrated in an outdoor mapping application involving a human operator, a ground and an air vehicle.

Learning articulated motion structures with Bayesian Networks

This paper presents a general methodology for learning articulated motions that, despite having non-linear correlations, are cyclical and have a defined pattern of behavior Using conventional algorithms to extract features from images, a Bayesian classifier is applied to cluster and classify features of the moving object. Clusters are then associated in different frames and structure learning algorithms for Bayesian networks are used to recover the structure of the motion. This framework is applied to the human gait analysis and tracking but applications include any coordinated movement such as multi-robots behavior analysis.

Dryness : the aesthetic condition of landscape design in Australia

Despite having a band of greenness around the edge, Australia is fundamentally a dry country. Australian vegetation has developed a high range of mechanisms to cope with the dryness, but after 200 years of white settlement, Australians still have not really come to terms with the real dryness of their country, and still exploit European paradigms that attempted to transplant European aesthetic conditions, greenness, to the brown land of Australia. Australia is going through serious water shortages that are still and will continue with the Greenhouse effect, to become a major factor in the location and extent of urbanisation, and also Australia's carrying capacity. While such aesthetic concerns might seem ornamental, until the population changes its attitude to the real condition of the country, it will keep using water and operating unsustainably. The design of the public landscape, however, offers the opportunity to contribute to changing people's aesthetic perception of the country, which might in turn help to redirect their water use practices. This essay develops a language for discussion dryness based around the experiences of water. After having developed this sensibility it then discusses a range of different approaches that landscape design in Australia has used to try to develop geographically appropriate design languages, including the Bush Garden and the Mediterranean Garden. It then discusses four design projects, one from the 1970's, the other three from the last five years that demonstrate what such an aesthetic might look like.

Improving accuracy and intelligibility of decisions

Intelligible and accurate risk-based decision-making requires a complex balance of information from different sources, appropriate statistical analysis of this information and consequent intelligent inference and decisions made on the basis of these analyses. Importantly, this requires an explicit acknowledgement of uncertainty in the inputs and outputs of the statistical model. The aim of this paper is to progress a discussion of these issues in the context of several motivating problems related to the wider scope of agricultural production. These problems include biosecurity surveillance design, pest incursion, environmental monitoring and import risk assessment. The information to be integrated includes observational and experimental data, remotely sensed data and expert information. We describe our efforts in addressing these problems using Bayesian models and Bayesian networks. These approaches provide a coherent and transparent framework for modelling complex systems, combining the different information sources, and allowing for uncertainty in inputs and outputs. While the theory underlying Bayesian modelling has a long and well established history, its application is only now becoming more possible for complex problems, due to increased availability of methodological and computational tools. Of course, there are still hurdles and constraints, which we also address through sharing our endeavours and experiences.

Development of an automated safety assessment framework for construction activities

This paper presents an ongoing research project concerning the development of an automated safety assessment framework for earthmoving and surface mining activities. This research seeks to determine data needs for safety assessment and investigates how to utilize collected data to promote more informed and efficient safety decision-making. The research first examined accidents and fatalities involved with earthmoving and surface mining activities—more specifically, those involving loading, hauling, and dumping operations,—investigated risk factors involved with the accidents, and finally identified data needs for safety assessment based on safety regulations and practices. An automated safety assessment method was then developed using the data needs that had been identified. This research is expected to contribute to the introduction of a fundamental framework for automated safety assessment and the systematic collection of safety-related data from construction activities. Implementation of the entire safety assessment process on actual construction sites remains a task for future research.

Asset life prediction and maintenance decision-making using a non-linear non-Gaussian state space model

Estimating and predicting degradation processes of engineering assets is crucial for reducing the cost and insuring the productivity of enterprises. Assisted by modern condition monitoring (CM) technologies, most asset degradation processes can be revealed by various degradation indicators extracted from CM data. Maintenance strategies developed using these degradation indicators (i.e. condition-based maintenance) are more cost-effective, because unnecessary maintenance activities are avoided when an asset is still in a decent health state. A practical difficulty in condition-based maintenance (CBM) is that degradation indicators extracted from CM data can only partially reveal asset health states in most situations. Underestimating this uncertainty in relationships between degradation indicators and health states can cause excessive false alarms or failures without pre-alarms. The state space model provides an efficient approach to describe a degradation process using these indicators that can only partially reveal health states. However, existing state space models that describe asset degradation processes largely depend on assumptions such as, discrete time, discrete state, linearity, and Gaussianity. The discrete time assumption requires that failures and inspections only happen at fixed intervals. The discrete state assumption entails discretising continuous degradation indicators, which requires expert knowledge and often introduces additional errors. The linear and Gaussian assumptions are not consistent with nonlinear and irreversible degradation processes in most engineering assets. This research proposes a Gamma-based state space model that does not have discrete time, discrete state, linear and Gaussian assumptions to model partially observable degradation processes. Monte Carlo-based algorithms are developed to estimate model parameters and asset remaining useful lives. In addition, this research also develops a continuous state partially observable semi-Markov decision process (POSMDP) to model a degradation process that follows the Gamma-based state space model and is under various maintenance strategies. Optimal maintenance strategies are obtained by solving the POSMDP. Simulation studies through the MATLAB are performed; case studies using the data from an accelerated life test of a gearbox and a liquefied natural gas industry are also conducted. The results show that the proposed Monte Carlo-based EM algorithm can estimate model parameters accurately. The results also show that the proposed Gamma-based state space model have better fitness result than linear and Gaussian state space models when used to process monotonically increasing degradation data in the accelerated life test of a gear box. Furthermore, both simulation studies and case studies show that the prediction algorithm based on the Gamma-based state space model can identify the mean value and confidence interval of asset remaining useful lives accurately. In addition, the simulation study shows that the proposed maintenance strategy optimisation method based on the POSMDP is more flexible than that assumes a predetermined strategy structure and uses the renewal theory. Moreover, the simulation study also shows that the proposed maintenance optimisation method can obtain more cost-effective strategies than a recently published maintenance strategy optimisation method by optimising the next maintenance activity and the waiting time till the next maintenance activity simultaneously.

Benchmarking local E-Government

Increasingly, almost everything we do in our daily lives is being influenced by information and communications technologies (ICTs) including the Internet. The task of governance is no exception with an increasing number of national, state, and local governments utilizing ICTs to support government operations, engage citizens, and provide government services. As with other things, the process of governance is now being prefixed with an “e”. E-governance can range from simple Web sites that convey basic information to complex sites that transform the customary ways of delivering all sorts of government services. In this respect local e-government is the form of e-governance that specifically focuses on the online delivery of suitable local services by local authorities. In practice local e-government reflects four dimensions, each one dealing with the functions of government itself. The four are: (a) e-services, the electronic delivery of government information, programs, and services often over the Internet; (b) e-management, the use of information technology to improve the management of government. This might range from streamlining business processes to improving the flow of information within government departments; (c) e-democracy the use of electronic communication vehicles, such as e-mail and the Internet, to increase citizen participation in the public decision-making process; (d) e-commerce, the exchange of money for goods and services over the Internet which might include citizens paying taxes and utility bills, renewing vehicle registrations, and paying for recreation programs, or government buying office supplies and auctioning surplus equipment (Cook, LaVigne, Pagano, Dawes, & Pardo, 2002). Commensurate with the rapid increase in the process of developing e-governance tools, there has been an increased interest in benchmarking the process of local e-governance. This benchmarking, which includes the processes involved in e-governance as well as the extent of e-governance adoption or take-up is important as it allows for improved processes and enables government agencies to move towards world best practice. It is within this context that this article discusses benchmarking local e-government. It brings together a number of discussions regarding the significance of benchmarking, best practices and actions for local e-government, and key elements of a successful local e-government project.

Integrated Acquisition Engineering Model for acquiring heavy engineering assets

In asset intensive industries such as mining, oil & gas, utilities etc. most of the capital expenditure happens on acquiring engineering assets. Process of acquiring assets is called as “Procurement” or “Acquisition”. An asset procurement decision should be taken in consideration with the installation, commissioning, operational, maintenance and disposal needs of an asset or spare. However, such cross-functional collaboration and communication does not appear to happen between engineering, maintenance, warehousing and procurement functions in many asset intensive industries. Acquisition planning and execution are two distinct parts of asset acquisition process. Acquisition planning or procurement planning is responsible for determining exactly what is required to be purchased. It is important that an asset acquisition decision is the result of cross-functional decision making process. An acquisition decision leads to a formal purchase order. Most costly asset decisions occur even before they are acquired. Therefore, acquisition decision should be an outcome of an integrated planning & decision making process. Asset intensive organizations both, Government and non Government in Australia spent AUD 102.5 Billion on asset acquisition in year 2008-09. There is widespread evidence of many assets and spare not being used or utilized and in the end are written off. This clearly shows that many organizations end up buying assets or spares which were not required or non-conforming to the needs of user functions. It is due the fact that strategic and software driven procurement process do not consider all the requirements from various functions within the organization which contribute to the operation and maintenance of the asset over its life cycle. There is a lot of research done on how to implement an effective procurement process. There are numerous software solutions available for executing a procurement process. However, not much research is done on how to arrive at a cross functional procurement planning process. It is also important to link procurement planning process to procurement execution process. This research will discuss ““Acquisition Engineering Model” (AEM) framework, which aims at assisting acquisition decision making based on various criteria to satisfy cross-functional organizational requirements. Acquisition Engineering Model (AEM) will consider inputs from corporate asset management strategy, production management, maintenance management, warehousing, finance and HSE. Therefore, it is essential that the multi-criteria driven acquisition planning process is carried out and its output is fed to the asset acquisition (procurement execution) process. An effective procurement decision making framework to perform acquisition planning which considers various functional criteria will be discussed in this paper.